Ontology highlight
ABSTRACT:
PROVIDER: PRJNA512999 | ENA |
REPOSITORIES: ENA
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Project description:The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and validated a collection of genomic datasets for eight Castanea species, 213 RNA-Seq samples, and 348 resequencing samples. These datasets are publicly available on figshare, providing a robust resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Additionally, the Castanea Genome Database (CGD, http://castaneadb.net) serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.
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Project description:The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and validated a collection of genomic datasets for eight Castanea species, 213 RNA-Seq samples, and 348 resequencing samples. These datasets are publicly available on figshare, providing a robust resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Additionally, the Castanea Genome Database (CGD, http://castaneadb.net) serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.
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Project description:The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and validated a collection of genomic datasets for eight Castanea species, 213 RNA-Seq samples, and 348 resequencing samples. These datasets are publicly available on figshare, providing a robust resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Additionally, the Castanea Genome Database (CGD, http://castaneadb.net) serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.
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Project description:The Chinese chestnut (Castanea mollissima) stands out as a plant with significant ecological and economic value, excellent nutritional quality and natural resistance to pests and diseases. Recent strides in high-throughput techniques have enabled the continuous accumulation of genomic data on chestnuts, presenting a promising future for genetic research and advancing traits in this species. To facilitate the accessibility and utility of this data, we have curated and validated a collection of genomic datasets for eight Castanea species, 213 RNA-Seq samples, and 348 resequencing samples. These datasets are publicly available on figshare, providing a robust resource for researchers studying Castanea genetics, functional genomics, and evolutionary biology. Additionally, the Castanea Genome Database (CGD, http://castaneadb.net) serves as a complementary platform, offering advanced data mining and analysis tools, including BLAST, Batch Query, GO/KEGG Enrichment Analysis, and Synteny Viewer, to enhance the usability of the curated datasets.
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Project description:Background: Evolutionary engineering is a powerful approach to isolate suppressor mutants and industrially relevant genotypes. Until recently, DNA microarray analysis was the only affordable genome-wide approach to identify the responsible mutations. This situation has changed due to the rapidly decreasing costs of whole genome (re)sequencing. DNA microarray-based mRNA expression analysis and whole genome resequencing were combined in a study on lactate transport in Saccharomyces cerevisiae. Jen1p is the only S. cerevisiae lactate transporter reported in literature. To identify alternative lactate transporters, a jen1Δ strain was evolved for growth on lactate. Results: Two independent evolution experiments yielded Jen1p-independent growth on lactate (μmax 0.14 and 0.18 h-1 for single-cell lines IMW004 and IMW005, respectively). Whereas mRNA expression analysis did not provide leads, whole-genome resequencing showed different single nucleotide changes (C755G/Leu219Val and C655G/Ala252Gly) in the acetate transporter gene ADY2. Analysis of mRNA levels and depth of coverage of DNA sequencing combined with karyotyping, gene deletions and diagnostic PCR showed that in IMW004 an isochromosome III (~475 kb), which contains two additional copies of ADY2C755G, was formed via crossover between YCLWΔ15 and YCRCΔ6. Introduction of the ADY2 alleles in a jen1 ady2 strain resulted in growth on lactate (μmax 0.14 h-1 for Ady2pLeu219Val and 0.12 h-1 for Ady2pAla252Gly). Conclusions: Whole-genome resequencing of yeast strains obtained from independent evolution experiments enabled rapid identification of a key gene that was not identified by mRNA expression analysis of the same strains. Reverse metabolic engineering showed that mutated alleles of ADY2 (C655G and C755G) encode efficient lactate transporters.
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